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Complexity with Heterogeneous Fundamentalists and a Multiplicative Price Mechanism

Author

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  • Ahmad K Naimzada

    (DISEI, Università degli studi di Firenze)

  • Giorgio Ricchiuti

    (DISEI, Università degli studi di Firenze)

Abstract

In contrast with the canonical models, Naimzada and Ricchiuti (2008, 2009) show that the interaction of groups of agents who have the same trading rule but present different beliefs about the fundamental value could be a source of instability in financial markets. Differently from Naimzada and Ricchiuti (2008, 2009), we assume the market maker employs a so-called multiplicative price mechanism (Tuinstra, 2002 and Zhu et al., 2009). We show that the occurrence of heterogeneity has an ambiguous role: it may either stabilize or destabilize the market.

Suggested Citation

  • Ahmad K Naimzada & Giorgio Ricchiuti, 2013. "Complexity with Heterogeneous Fundamentalists and a Multiplicative Price Mechanism," Working Papers - Economics wp2013_03.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    • Handle: RePEc:frz:wpaper:wp2013_03.rdf
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    References listed on IDEAS

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    1. Simone Bertoli & Giampiero Gallo & Giorgio Ricchiuti, 2010. "Exchange market pressure: some caveats in empirical applications," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2435-2448.
    2. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    3. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    4. Kaltwasser, Pablo Rovira, 2010. "Uncertainty about fundamentals and herding behavior in the FOREX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1215-1222.
    5. Zhu, Mei & Chiarella, Carl & He, Xue-Zhong & Wang, Duo, 2009. "Does the market maker stabilize the market?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3164-3180.
    6. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    7. Westerhoff, Frank & Reitz, Stefan, 2005. "Commodity price dynamics and the nonlinear market impact of technical traders: empirical evidence for the US corn market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 641-648.
    8. Naimzada, Ahmad K. & Ricchiuti, Giorgio, 2009. "Dynamic effects of increasing heterogeneity in financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1764-1772.
    9. Ahmad Naimzada & Giorgio Ricchiuti, 2006. "Heterogeneous Fundamentalists and Imitative Processes," Working Papers 104, University of Milano-Bicocca, Department of Economics, revised Nov 2006.
    10. Westerhoff, Frank H., 2004. "Greed, fear and stock market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 635-642.
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    Cited by:

    1. Carraro, Alessandro & Ricchiuti, Giorgio, 2015. "Heterogeneous fundamentalists and market maker inventories," Chaos, Solitons & Fractals, Elsevier, vol. 79(C), pages 73-82.
    2. Giovanni Campisi & Silvia Muzzioli & Fabio Tramontana, 2021. "Uncertainty about fundamental, pessimistic and overconfident traders: a piecewise-linear maps approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 707-726, December.
    3. F. Cavalli & A. Naimzada & M. Pireddu, 2017. "An evolutive financial market model with animal spirits: imitation and endogenous beliefs," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1007-1040, November.

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    More about this item

    Keywords

    mathematical economics; chaos; heterogeneous interacting agents; financial markets.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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